基于MATLAB的BP神经网络模型在漠阳江水质评价中的应用研究

为提高水质评价的准确性,基于MATLAB及人工神经网络理论,采用误差反向传播的BP算法建立漠阳江水质评价模型,充分利用神经网络的非线性映射特性,取7项常规地表水水质评价指标对漠阳江水质进行评价,并将BP神经网络评价结果与单因子评价法及综合指数法的评价结果进行比较,网络运行结果表明一致效果良好.同时较传统的水质评价方法,该网络具有较高的识别精度,提高了水质评价等级的准确性,使评价的结果更具有科学性.     

低碳物流发展现状及对策研究

在低碳经济日益发展的今天,物流业的低碳化发展存在的问题需要我们正视：低碳物流相关法规不完善;物流企业技术装备较落后、标准化水平不高,致使能源使用效率低下;低碳物流教育未有效开展;社会公众的低碳化意识较弱。对以上问题可采取的对策有：政府应完善低碳物流相关法规,健全碳交易体系,实行有效激励;物流行业应加快低碳技术的研发及推广,推进低碳物流系统工程;低碳物流教育应逐步有效开展;加强宣传,提高公众低碳物流意识。     

瑞士土壤环境监测网络构建与运行对中国的启示

“十三五”期间,中国初步构建了国家土壤环境监测网并开展了监测工作。当前,国家层面土壤环境监测网络的构建和运行还处于起步阶段,笔者选取土壤环境监测开展较为成熟的瑞士土壤环境监测网(NABO)作为研究对象,综述了NABO的技术体系及多年来的土壤环境监测结果,并结合中国土壤环境监测工作现状进行讨论,认为NABO在监测网络建立、指标选取、数据分析等方面建立了较为成熟的技术体系,未来中国国家土壤环境监测网可在此方面借鉴瑞士经验。     

FTA在城市控制爆破工程事故中的运用

城市控制爆破工程采用电雷管网路起爆,极易发生爆破事故.运用FTA方法,编制了爆破事故树,并进行了定性分析.结合工程实际,提出了爆破事故的具体预防措施,更依法采取了爆破安全管理措施.     

Source characterization of ambient fine particles at multiple sites in the Seattle area

To identify major PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) sources with a particular emphasis on the ship engine emissions from a major port, integrated 24 h PM_2.5 speciation data collected between 2000 and 2005 at five United State Environmental Protection Agency's Speciation Trends Network monitoring sites in Seattle, WA were analyzed. Seven to ten PM_2.5 sources were identified through the application of positive matrix factorization (PMF). Secondary particles (12–26% for secondary nitrate; 17–20% for secondary sulfate) and gasoline vehicle emissions (13–31%) made the largest contributions to the PM_2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM_2.5 mass (31%). Other identified sources include diesel vehicle emissions, airborne soil, residual oil combustion, sea salt, aged sea salt, metal processing, and cement kiln. Residual oil combustion sources identified at multiple monitoring sites point clearly to the Port of Seattle suggesting ship emissions as the source of oil combustion particles. In addition, the relationship between sulfate concentrations and the oil combustion emissions indicated contributions of ship emissions to the local sulfate concentrations. The analysis of spatial variability of PM_2.5 sources shows that the spatial distributions of several PM_2.5 sources were heterogeneous within a given air shed.     

基于BP神经网络的垃圾焚烧过程故障诊断

应用BP神经网络方法,建立了垃圾焚烧过程故障诊断的模型.该方法采用梯度下降法训练网络权值,利用最优停止法对网络进行了优化,避免了过拟合现象.提高了BP神经网络的训练速度和泛化能力.并以实际焚烧过程工况数据进行性能检验,检验结果表明了该BP网络具有较高的诊断精度.     

基于神经网络的洪水预报研究

人工神经网络通过神经元之间的相互作用来完成整个网络的信息处理,具有自学习和自适应等一系列优点,因而用它来进行洪水预报是可行的.对洪水预报问题,初步建立了基于神经网络的洪水预报系统,给出了应用实例.     

Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.     

毛竹林各组分能量估算模型的研究

在建瓯设置40块毛竹林标准地,分别测定了毛竹单株各部分干重与能量,建立了各部分生物量模型,并在此基础上,运用人工神经网络方法对毛竹林各组分能量进行估测.结果表明毛竹林各组分秆、枝叶和地下部分的平均能量依次为4.23225×10     

京津冀地区一次污染过程的星载地基激光雷达联合观测分析

针对2018年3月9—15日京津冀地区的一次空气重污染过程,进行了基于地基颗粒物激光雷达组网的星载-地基联合观测分析。颗粒物激光雷达观测到污染前期为局地污染累积过程,中期有明显的污染物区域传输过程,北京受太行山沿线城市污染输送影响较大。风廓线激光雷达观测结果表明:此次污染过程近地面主要为偏南风且风力较弱,冷空气到来时风向转为较强东北风,导致污染消散。微波辐射计观测到保定在污染过程中出现持续6 d的逆温层,同时在污染过程中近地面相对湿度较高,逆温层被打破后污染开始消散。在污染过程的各个阶段中,污染团的空间分布与变化特征均被很好地反映出来,可见地天联合观测对污染物的累积与输送研究有较大的意义,能对京津冀及周边地区的大气污染联防联控提供有力支持。